Work

Running the Dual-PQC GAN on noisy simulators and real quantum hardware

Year: 2023

Type: conference-paper

Abstract: In an earlier work [1], we introduced dual-Parameterized Quantum Circuit (PQC) Generative Adversarial Networks (GAN), an advanced prototype of quantum GAN. We applied the model on a realistic High-Energy Physics (HEP) use case: the exact theoretical simulation of a calorimeter response with a reduced problem size. This paper explores the dual-PQC GAN for a more practical usage by testing its performance in the presence of different types of quantum noise, which are the major obstacles to overcome for successful deployment using near-term quantum devices. The results propose the possibility of running the model on current real hardware, but improvements are still required in some areas.

Source: Journal of Physics Conference Series

DOI: 10.1088/1742-6596/2438/1/012062

Authors: Su Yeon Chang, Edwin Agnew, Elías Combarro, Michele Grossi, Steven Herbert, Sofia Vallecorsa

Institutions: École Polytechnique Fédérale de Lausanne, European Organization for Nuclear Research, Universidad de Oviedo, University of Cambridge

Language: English

Topic: Quantum Computing Algorithms and Architecture

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

Funders: Amazon Web Services, Gobierno del Principado de Asturias, CERN, Agencia Estatal de Investigación

Awards: G2971188108, G3480869486, G4526231891, G5080475149, G7084143925